Photo-enhanced output in memdiode devices based on hybrid materials

The discovery of photo-enhanced outputs in the fabricated memdiodes based on metal halide-embedded polymeric hybrid composites has meaningful and practical implications. The two-terminal devices exhibit typical rectifying characteristics, similar to a standard pn junction diode, with unusual photo-enhanced charge transportation and hysteresis behaviors. The MDs consist of an active layer of blended organic–inorganic hybrid material [a mixture of CuCl2 and polyethylene glycol (PEG)] deposited on a layer of pure polymer (polymethyl methacrylate) and, in turn, on a rigid substrate (ITO glass or Si wafer). It is found that the photoinduced current increases hundreds of times in magnitude on the ITO glass-substrate sample, much higher than that of the Si-substrate sample. The substrate-dependent photocurrent can be attributed to charge carrier generation by optical absorption correlated with transport paths at different interfaces and variations of working areas by different substrates. The energy bandgaps extrapolated from the UV–Vis absorption spectroscopy are at 1.50 and 3.1 eV, consistent with two applied voltages at which the currents jump abruptly under light-on and light-off statuses, respectively. The study of time-dependent resistances displays an exponential decay, a memristive feature, and a long relaxation time between high-resistance and low-resistance. The memdiodes are stable with repeatable working values in a bio-applicable range, assuring that the hybrid materials are excellent candidates for potential applications in biomedical electronic circuits, artificial neuromorphic synapses, and brain-inspired quantum computing.

Authors

Institutions

Publication Details

Journal
AIP Advances
Published
2025-03-01
DOI
https://doi.org/10.1063/5.0255460
Citations
1
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.73

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Photo-enhanced output in memdiode devices based on hybrid materials

Jacob Lee, Xiaojuan Fan, Prabir Patra
1 citations
AIP Advances
Advanced Memory and Neural Computing
0.73
article

Photo-enhanced output in memdiode devices based on hybrid materials

Jacob Lee, Xiaojuan Fan, Prabir Patra
article en
1 citations

Abstract

The discovery of photo-enhanced outputs in the fabricated memdiodes based on metal halide-embedded polymeric hybrid composites has meaningful and practical implications. The two-terminal devices exhibit typical rectifying characteristics, similar to a standard pn junction diode, with unusual photo-enhanced charge transportation and hysteresis behaviors. The MDs consist of an active layer of blended organic–inorganic hybrid material [a mixture of CuCl2 and polyethylene glycol (PEG)] deposited on a layer of pure polymer (polymethyl methacrylate) and, in turn, on a rigid substrate (ITO glass or Si wafer). It is found that the photoinduced current increases hundreds of times in magnitude on the ITO glass-substrate sample, much higher than that of the Si-substrate sample. The substrate-dependent photocurrent can be attributed to charge carrier generation by optical absorption correlated with transport paths at different interfaces and variations of working areas by different substrates. The energy bandgaps extrapolated from the UV–Vis absorption spectroscopy are at 1.50 and 3.1 eV, consistent with two applied voltages at which the currents jump abruptly under light-on and light-off statuses, respectively. The study of time-dependent resistances displays an exponential decay, a memristive feature, and a long relaxation time between high-resistance and low-resistance. The memdiodes are stable with repeatable working values in a bio-applicable range, assuring that the hybrid materials are excellent candidates for potential applications in biomedical electronic circuits, artificial neuromorphic synapses, and brain-inspired quantum computing.

AIP AdvancesVol. 15(3)
Marshall University (US)
West Virginia Science and Research, West Virginia Higher Education Policy Commission
Openalex Percentile: Top 30%
Advanced Memory and Neural Computing
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.